Spectral flow cytometry for detecting DNA cargo in malaria parasite–derived extracellular vesicles
Bibliographic record
Abstract
Cells across biological kingdoms release extracellular vesicles (EVs) as a means of communication with other cells, be their friends or foes. This is indeed true for the intracellular malaria parasite Plasmodium falciparum (Pf), which utilizes EVs to transport bioactive molecules to various human host systems. Yet, the study of this mode of communication in malaria research is currently constrained due to limitations in high-resolution tools and the absence of commercial antibodies. Here, we demonstrate the power of an advanced spectral flow cytometry approach to robustly detect secreted EVs, isolated from Pf-infected red blood cells. By labeling both EV membrane lipids and the DNA cargo within (non-antibody staining approach), we were able to detect a subpopulation of parasitic-derived EVs enriched in DNA. Furthermore, we could quantitatively measure the DNA-carrying EVs isolated from two distinct blood stages of the parasite: rings and trophozoites. Our findings showcase the potential of spectral flow cytometry to monitor dynamic changes in nucleic acid cargo within pathogenic EVs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".